Data Science and Artificial Intelligence for Responsible Recommendations-Reference-Cited by-同舟云学术

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Data Science and Artificial Intelligence for Responsible Recommendations

Published:2022-08-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Wang Shoujin¹,Liu Ninghao²,Zhang Xiuzhen³,Wang Yan⁴,Ricci Francesco⁵,Mobasher Bamshad⁶

Affiliation:

1. RMIT University, Macquarie University, Melbourne, Sydney, UNK, Australia

2. University of Georgia, Athens, GA, USA

3. RMIT University, Melbourne, UNK, Australia

4. Macquarie University, Sydney, UNK, Australia

5. Free University of Bozen-Bolzano, Bolzano, UNK, Italy

6. DePaul University, Chicago, IL, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3542916

Reference4 articles.

1. Toward trustworthy recommender systems

2. Hierarchical Attentive Transaction Embedding With Intra- and Inter-Transaction Dependencies for Next-Item Recommendation

3. Shoujin Wang Liang Hu Longbing Cao and etal 2018. Attention-based transactional context embedding for next-item recommendation. In AAAI. 2532--2539. Shoujin Wang Liang Hu Longbing Cao and et al. 2018. Attention-based transactional context embedding for next-item recommendation. In AAAI. 2532--2539.

4. Shoujin Wang Xiaofei Xu Xiuzhen Zhang Yan Wang and Wenzhuo Song. 2022. Veracity-aware and event-driven personalized news recommendation for fake news mitigation. In WWW. 3673--3684. Shoujin Wang Xiaofei Xu Xiuzhen Zhang Yan Wang and Wenzhuo Song. 2022. Veracity-aware and event-driven personalized news recommendation for fake news mitigation. In WWW. 3673--3684.

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Hybrid Automatic Multistage Recommendation Techniques for Social Media Networks;2023 International Conference on Computational Intelligence, Networks and Security (ICCINS);2023-12-22

2. Trustworthy Recommender Systems;ACM Transactions on Intelligent Systems and Technology;2023-10-13

3. Data science for next-generation recommender systems;International Journal of Data Science and Analytics;2023-06-29

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